Nvidia's KV Cache Transform Coding (KVTC) compresses LLM key-value cache by 20x without model changes, cutting GPU memory costs and time-to-first-token by up to 8x for multi-turn AI applications.
Detect your hardware and find out which AI models you can run locally. GPU, CPU, and RAM analysis in your browser.
Designing AI Chip Hardware and Software Bjarke Hammersholt Roune 2026 This document is, for now, open for comments. You can use the Google Docs comment feature to add comments anywhere. Thanks! What is this document? I was going to start an AI chip company and this document…
Cambridge Researchers Introduce SymTorch: A PyTorch Library that Translates Deep Learning Models into Human-Readable Equations
Use Claude Code to speed up data science. Master data cleaning, visualization, and model prototyping with Python, pandas, and scikit-learn. Get actionable power tips.
The definitive 100+ page guide to the thermodynamics, scarcity, and heavy assets powering the AI revolution.
Amazon shortened GPU depreciation while Meta extended it—same month, same technology. The $3.6B divergence exposes the accounting discretion behind AI infrastructure economics.
Nvidia researchers developed dynamic memory sparsification (DMS), a technique that compresses the KV cache in large language models by up to 8x while maintaining reasoning accuracy — and it can be retrofitted onto existing models in hours.
Google just open-sourced their MCP server for databases. Connect any database to any AI agent in 10 lines of code. It's called MCP Toolbox. What it handles: → Connection pooling → Authentication → Query execution → Tool generation → OpenTelemetry tracing Supported databases: →…
Goose, Block’s open-source AI coding agent, is emerging as a free alternative to Anthropic’s Claude Code, as developers weigh offline control, rate limits, and the rising cost of AI coding tools.
In this article, I’ll walk you through a guided project to add reasoning skills to your LLM apps. Add Reasoning Skills to Your LLM Apps.
Note: Looking at the equations above, if T<0T<0 then the sign of the exponent flips. That means that the states that were previously the least likely are now the most likely, and vice versa. As temperature approaches zero from the negative side, the model output will again be deterministic — but this time, the least likely tokens will be output.
Looking at the equations above, if T<0T < 0T<0 then the sign of the exponent flips. That means that the states that were previously the least likely are now the most likely, and vice versa. As temperature approaches zero from the negative side, the model output will again be deterministic — but…
From DeepSeek-V3 to Kimi K2: A Look At Modern LLM Architecture Design
Search for models on Ollama.
Co-Packaged Optics (CPO) has long promised to transform datacenter connectivity, but it has taken a long time for the technology to come to market, with tangible deployment-ready products only arriving in 2025.
copper-based scale-up solutions, such as NVLink, provide tremendous bandwidth of 7.2 Tbit/s per GPU – soon to be 14.4 Tbit/s per GPU in the Rubin generation, yet copper-based links are limited in range to two meters
Rubin
This is the third in my annual series reviewing everything that happened in the LLM space over the past 12 months. For previous years see Stuff we figured out about …
It turned out that the real unlock of reasoning was in driving tools.
notable result is that AI assisted search actually works now.
Understanding GRPO and New Insights from Reasoning Model Papers
the muted response to GPT-4.5 and Llama 4 (non-reasoning) models suggests we are approaching the limits of what scaling model size and data alone can achieve.
A 2025 review of large language models, from DeepSeek R1 and RLVR to inference-time scaling, benchmarks, architectures, and predictions for 2026.
DeepSeek released their R1 paper in January 2025, which showed that reasoning-like behavior can be developed with reinforcement learning, it was a really big deal
DeepSeek R1 was released as an open-weight model
In this article, I’ll walk you through a complete guide to LangGraph from the ground up. LangGraph Explained from Scratch.
In LangChain, this usually means moving from user input to a prompt, then to the LLM, and finally to the output
ollama pull llama3
Tech giants including Meta, Alphabet, Microsoft and Amazon have all extended the estimated useful lives of their servers and AI equipment over the past five years, sparking a debate among investors about whether these accounting changes are artificially inflating profits. Meta…
Compare the top 7 large language models and systems for coding in 2025. Discover which ones excel for software engineering tasks.
OpenAI GPT-5 / GPT-5-Codex Anthropic Claude 3.5 Sonnet / Claude 4.x Sonnet with Claude Code Google Gemini 2.5 Pro Meta Llama 3.1 405B Instruct DeepSeek-V2.5-1210 (with DeepSeek-V3 as the successor) Alibaba Qwen2.5-Coder-32B-Instruct Mistral Codestral 25.01
Core coding quality: HumanEval, MBPP / MBPP EvalPlus, code generation and repair quality on standard Python tasks. Repo and bug-fix performance: SWE-bench Verified (real GitHub issues), Aider Polyglot (whole-file edits), RepoBench, LiveCodeBench. Context and long-context behavior: Documented…
From DeepSeek-V3 to Kimi K2: A Look At Modern LLM Architecture Design
this section, I’ll focus on two key architectural techniques introduced in DeepSeek V3 that improved its computational efficiency and distinguish it from many other LLMs:
Multi-Head Latent Attention (MLA)
Codes/Notebooks for AI Projects. Contribute to Marktechpost/AI-Tutorial-Codes-Included development by creating an account on GitHub.
In this article, I'll take you through a step-by-step guide to fine-tuning LLMs with LoRA. A Guide to Fine-Tuning LLMs using LoRA.
Multiple-Choice Benchmarks, Verifiers, Leaderboards, and LLM Judges with Code Examples
four common ways of evaluating trained LLMs in practice: multiple choice, verifiers, leaderboards, and LLM judges
training loss, perplexity, and rewards, but they are usually used internally during model development.)
How LoRA matches full training performance more broadly than expected
How we spent under half a million dollars to build a 30 petabyte data storage cluster in downtown San Francisco
Compare top local LLMs for 2025: context windows, VRAM tiers, licenses, quantization, runtimes, dense vs MoE tradeoffs clearly
Semantic search and document parsing tools for the command line - run-llama/semtools
Note: (venv) bjpcjp@Sword15-A12UE:~/projects$ cargo install semtools Updating crates.io index error: failed to download `semtools v1.2.1` Caused by: unable to get packages from source Caused by: failed to download replaced source registry `crates-io` Caused by: failed to parse manifest at `/home/bjpcjp/.cargo/registry/src/index.crates.io-6f17d22bba15001f/semtools-1.2.1/Cargo.toml` Caused by: feature…
Best viewed on desktops. On a phone screen, some columns are hidden. When a new repo is indexed, changes in stars in the last day/week are default to 0. Full analysis: What I learned from...
80x Faster Python? Discover How One Line Turns Your Code Into a GPU Beast!
Transcribe PDFs with local LLMs
New research reveals open-source AI models use up to 10 times more computing resources than closed alternatives, potentially negating cost advantages for enterprise deployments.
Comparison and analysis of AI models and API hosting providers. Independent benchmarks across key performance metrics including quality, price, output speed & latency.
A new study from Anthropic introduces "persona vectors," a technique for developers to monitor, predict and control unwanted LLM behaviors.
How Language Models Turn Text into Meaning, From Traditional
In this article, I'll take you through the complete LLM tech stack you should know to develop & deploy real-world LLM applications.
The latest in LLM research with a hand-curated, topic-organized list of over 200 research papers from 2025.
Structural challenges and the nation’s many languages have made it tough to develop foundational AI models. But the government is keen not to be left behind.
Coders' Colaboratory mini-hackathon on `llm` by simonw - llm-hackathon.md
Ready to become a certified watsonx AI Assistant Engineer? Register now and use code IBMTechYT20 for 20% off of your exam → https://ibm.biz/Bdnd3dLearn more ...
Get a quick overview of GPT, BERT, LLaMA, and more!
TL;DR: I developed a simple, open-source benchmark to test if LLM agents follow high-level safety principles when they conflict with a given task acc…
* Introduction * Understanding vs. Generation in Vision * Unifying Vision – Are We There Yet? * Vision Without Words: Do Models Need Language? *…
Anthony Shaw's [llm-github-models](https://github.com/tonybaloney/llm-github-models) plugin just got an upgrade: it now supports [LLM 0.26 tool use](https://simonwillison.net/2025/May/27/llm-tools/) for a subset of the models hosted on the [GitHub Models…
LLM 0.26 is out with the biggest new feature since I started the project: support for tools. You can now use the LLM CLI tool—and Python library—to grant LLMs from …
